The Influence of Alliance Innovation Network Structure upon Enterprise Innovation: A Case Study of China’s Energy-Saving and Environment-protection Industry

Meng Xu

doi:10.5539/ijbm.v13n2p208

Abstract

The Energy-saving and environment-protection industry, an important strategic and emerging industry in China, will develop into a pillar industry. In view of global climate change, environmental pollution, resource depletion and the defects and deficiencies in traditional technology, technology and product innovation constitute the lifeline of energy-saving and environment-protection industry. The alliance network of enterprises will influence, stimulate, and regulate enterprise innovation greatly. A comprehensive analysis of alliance data of China's energy-saving and environment-protection industry from 2000 to 2013 by using Ucinet software can reveal the network structure parameters such as degree, clique number, average path length, clustering coefficient, and betweenness centrality, which reflects different types of enterprise networks and different positions of enterprises in different types of networks. A negative regression analysis of enterprise patent data and network structure parameters by using Stata software can make some conclusions that the influences of network characteristics on enterprise innovation reach the maximum in the second year of the window period end, that innovation accumulation, clustering coefficient, betweenness centrality are related to the enterprise innovation, that clique number, network density are negatively related to the enterprise innovation, and that there is an inverted U relationship between average path length and enterprise innovation. It is suggested to increase the accumulation level of innovation, appropriately control the network density, reduce the average path length, improve the betweenness centrality and clustering coefficient of enterprises, so as to improve the overall innovation level.

Highlights

1.1 Research BackgroundInnovation is the main way for enterprises and countries to gain competitiveness, and the main means for enterprises to obtain excess profits
A negative regression analysis of enterprise patent data and network structure parameters by using Stata software can make some conclusions that the influences of network characteristics on enterprise innovation reach the maximum in the second year of the window period end, that innovation accumulation, clustering coefficient, betweenness centrality are related to the enterprise innovation, that clique number, network density are negatively related to the enterprise innovation, and that there is an inverted U relationship between average path length and enterprise innovation
Zhao Yan et al think that the network centrality of enterprises has an lagged positive effect on enterprise innovation(Zhao, 2017); the small world of strategic alliance network positively influences innovation performance (Zhao, 2013); the non redundant links and aggregation of enterprise alliance network nodes have a potential impact on enterprise innovation (Zhao, 2013); the structure holes of the alliance network can significantly promote the innovation performance of enterprises(Zhao, 2012); faction and knowledge flow have positive influence on alliance network innovation performance (Zhao, 2016)

Summary

Introduction

1.1 Research BackgroundInnovation is the main way for enterprises and countries to gain competitiveness, and the main means for enterprises to obtain excess profits. Many Chinese enterprises with foreign businesses are not in the key link of the global industry chain, and their product pricing ability is weak and the added value of production is low. As a result, they are subject to other enterprises. 1.1.1 Innovation Costs and Risks Require Enterprise Alliance Cooperation. Enterprises gain competitive advantage by their technology and innovation. It requires a lot of money, manpower and time. With the deepening of postwar economic globalization, more and more enterprises begin to form strategic alliances to share resources and increase mutual innovation advantages.

Methods

Results

Conclusion